Welfare implications of learning through solicitation versus diversification in health care

Anirban Basu

Journal of Health Economics, 2015, vol. 42, issue C, 165-173

Abstract: Using Roy's model of sorting behavior, I study welfare implications of learning about medical care quality through the current health care data production infrastructure that relies on solicitation of research subjects. Due to severe adverse-selection issues, I show that such learning could be biased and welfare decreasing. Direct diversification of treatment receipt may solve these issues but is infeasible. Unifying Manski's work on diversified treatment choice under ambiguity and Heckman's work on estimating heterogeneous treatment effects, I propose a new infrastructure based on temporary diversification of access that resolves the prior issues and can identify nuanced effect heterogeneity.

Keywords: Learning; Diversification; Comparative effectiveness research; Economic evaluation; Instrumental variables; Heterogeneity (search for similar items in EconPapers)
JEL-codes: C1 C9 D6 I1 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167629615000387
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Welfare Implications of Learning Through Solicitation versus Diversification in Health Care (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jhecon:v:42:y:2015:i:c:p:165-173

DOI: 10.1016/j.jhealeco.2015.04.001

Access Statistics for this article

Journal of Health Economics is currently edited by J. P. Newhouse, A. J. Culyer, R. Frank, K. Claxton and T. McGuire

More articles in Journal of Health Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().